Example usage for java.util.stream Collectors groupingBy

Introduction

In this page you can find the example usage for java.util.stream Collectors groupingBy.

Prototype

public static <T, K, A, D> Collector<T, ?, Map<K, D>> groupingBy(Function<? super T, ? extends K> classifier,
        Collector<? super T, A, D> downstream)

Source Link

Document

Returns a Collector implementing a cascaded "group by" operation on input elements of type T , grouping elements according to a classification function, and then performing a reduction operation on the values associated with a given key using the specified downstream Collector .

Usage

From source file:Main.java

public static void main(String[] args) {
    Map<Employee.Gender, DoubleSummaryStatistics> incomeStatsByGender = Employee.persons().stream().collect(
            Collectors.groupingBy(Employee::getGender, Collectors.summarizingDouble(Employee::getIncome)));

    System.out.println(incomeStatsByGender);
}

From source file:Main.java

public static void main(String[] args) {
    Map<Month, String> dobCalendar = Employee.persons().stream()
            .collect(Collectors.collectingAndThen(Collectors.groupingBy(p -> p.getDob().getMonth(),
                    Collectors.mapping(Employee::getName, Collectors.joining(" "))), result -> {
                        for (Month m : Month.values()) {
                            result.putIfAbsent(m, "None");
                        }//from w w w . j  av a  2s. com
                        return Collections.unmodifiableMap(new TreeMap<>(result));
                    }));

    dobCalendar.entrySet().forEach(System.out::println);
}

From source file:Main.java

public static void main(String[] args) {
    List<Person> roster = createRoster();

    System.out.println("Total age by gender:");
    Map<Person.Sex, Integer> totalAgeByGender = roster.stream().collect(
            Collectors.groupingBy(Person::getGender, Collectors.reducing(0, Person::getAge, Integer::sum)));

    List<Map.Entry<Person.Sex, Integer>> totalAgeByGenderList = new ArrayList<>(totalAgeByGender.entrySet());

    totalAgeByGenderList.stream()/*  w w  w  . ja  v a 2s .c  om*/
            .forEach(e -> System.out.println("Gender: " + e.getKey() + ", Total Age: " + e.getValue()));

}

From source file:Main.java

public static void main(String[] args) {
    List<Person> roster = createRoster();

    System.out.println("Names by gender:");
    Map<Person.Sex, List<String>> namesByGender = roster.stream().collect(
            Collectors.groupingBy(Person::getGender, Collectors.mapping(Person::getName, Collectors.toList())));

    List<Map.Entry<Person.Sex, List<String>>> namesByGenderList = new ArrayList<>(namesByGender.entrySet());

    namesByGenderList.stream().forEach(e -> {
        System.out.println("Gender: " + e.getKey());
        e.getValue().stream().forEach(f -> System.out.println(f));
    });/*ww  w .  ja v a  2s.  com*/

}

From source file:Main.java

/**
 * Returns a collector that computes the distribution of the provided elements. This effectively counts how many
 * times an item has appeared in a stream.
 *
 * @param <T>/*from   w  w  w .  jav a  2  s  .c om*/
 *            the counted type
 * @return the distribution collector
 */
public static <T> Collector<T, ?, Map<T, Long>> distribution() {
    return Collectors.groupingBy(Function.identity(), Collectors.counting());
}

From source file:com.firewallid.util.FIUtils.java

public static <L> Map<L, Long> reduceListToMap(List<L> l) {
    Map<L, Long> map = l.parallelStream()
            .collect(Collectors.groupingBy(object -> object, Collectors.counting()));

    return map;//from  w w w.  java  2 s.  c o m
}

From source file:com.firewallid.util.FIUtils.java

public static <U, V extends Number> List<Tuple2<U, Double>> sumList(List<Tuple2<U, V>> l1,
        List<Tuple2<U, V>> l2) {
    l1.addAll(l2);/*ww w.  j  a  va 2s .  c o m*/
    List<Tuple2<U, Double>> sum = l1.parallelStream()
            .collect(Collectors
                    .groupingBy(data -> data._1(), Collectors.mapping(data -> data._2(), Collectors.toList())))
            .entrySet().parallelStream()
            .map(data -> new Tuple2<>(data.getKey(),
                    data.getValue().parallelStream().mapToDouble(value -> value.doubleValue()).sum()))
            .collect(Collectors.toList());

    return sum;
}

From source file:com.create.validation.PropertyValidationErrorsProvider.java

private Map<String, List<String>> getPropertyValidationErrorsGroupedByNestedPath(
        List<ObjectError> objectErrors) {
    return objectErrors.stream().map(this::toPropertyValidationError)
            .collect(Collectors.groupingBy(PropertyValidationError::getNestedPath,
                    Collectors.mapping(PropertyValidationError::getMessage, Collectors.toList())));
}

From source file:eu.cloudwave.wp5.feedbackhandler.aggregations.strategies.SimpleRequestAggregationStrategyImpl.java

/**
 * {@inheritDoc}/*from  ww  w .j a va2 s.  c om*/
 */
@Override
public RequestAggregationValues aggregate(RequestCollector requests) {

    IntSummaryStatistics stats = requests.getReqTimestamps().stream()
            .collect(Collectors.groupingBy(
                    timestamp -> DateUtils.round(new Date(timestamp), timestampAggregation),
                    Collectors.counting()))
            .values().stream().mapToInt(p -> toInt(p)).summaryStatistics();

    return new RequestAggregationValuesImpl(stats.getMin(), stats.getMax(), stats.getAverage(), stats.getSum(),
            stats.getCount());
}

From source file:eu.cloudwave.wp5.feedbackhandler.repositories.aggregations.AggregatedMicroserviceClientRequest.java

public IntSummaryStatistics getStatistics() {
    // Map<Date, Long> groupedRequests = microserviceClientRequest.getReqTimestamps().stream()
    // .collect(Collectors.groupingBy(timestamp -> DateUtils.round(new Date(timestamp), timestampAggregation),
    // Collectors.counting()));

    return microserviceClientRequest.getReqTimestamps().stream()
            .collect(Collectors.groupingBy(
                    timestamp -> DateUtils.round(new Date(timestamp), timestampAggregation),
                    Collectors.counting()))
            .values().stream().mapToInt(p -> toInt(p)).summaryStatistics();
}